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Predictive Data Mining
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Produktbeschreibungen
Amazon.com
Data mining is a hot technology, and this short, authoritative guide shows how it works and why it is gaining ground in the worlds of finance, manufacturing, marketing, and health care. The book begins by exploring the links between "big data"--the data warehouse built up of multiple databases--and traditional statistics. (The authors defend the methods of big data against traditional statistics, which has usually relied on smaller samples. However, they also look at the sources of error in both disciplines.)
The authors then look at the nuts and bolts of the data-mining process. They show how data must be prepared--sometimes reduced--in order to be manageable, and they define the important features. They show how the actual analysis of data mining can be as simple as adding up scores for selected features or how it can use statistical methods or even neural networks. (For some problems, the features themselves aren't known ahead of time; data mining can be used to discover these features automatically.) The authors then discuss how to interpret the results of analysis so that predictions can be made for new cases based on old ones.
The book concludes with short scenarios of how data mining can be applied, with examples drawn from manufacturing, health care, marketing, and publishing. The authors show the strengths--and limits--of data mining and argue that faster hardware and greater database storage capabilities will make this technology more widely used. Though it is written by two researchers in the field, Predictive Data Mining is suitable for general readers who are interested in the topic. --Richard V. Dragan
Pressestimmen
"I enjoy reading PREDICTIVE DATA MINING. It presents an excellent perspective on the theory and practice of data mining. It can help educate statisticians to build alliances between statisticians and data miners." --Emanuel Parzen, Distinguished Professor of Statistics, Texas A&M University
In diesem Buch
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Einleitungssatz
Data mining is the search for valuable information in large volumes of data. Lesen Sie die erste Seite
Buchdeckel | Copyright | Inhaltsverzeichnis | Auszug | Stichwortverzeichnis | Rückseite
Data mining is the search for valuable information in large volumes of data. Lesen Sie die erste Seite
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Buchdeckel | Copyright | Inhaltsverzeichnis | Auszug | Stichwortverzeichnis | Rückseite
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Format:Taschenbuch
I felt that this was an excellent intorduction to an area otherwise overcrowded with untested and semi validated "methodologies". I loved the fact that this title is not vendor specific (unlike some other titles trying to sell you tools or what!). Seeing the MKP name on it is reassuring. Would'nt hesitate to recommend this one!
Format:Taschenbuch
This book covers many different types of techniques for data mining but doesn't give lots of details on some of the techniques. I was looking for inductive learning algorihtms (ID3, C4.5, C5.0) and didn't find them here. For the techniques with depth the depth is in the form of formulas rather than examples.
Format:Taschenbuch
If you are new to the field I definitely think this is a good introduction to the main topics revolving around getting more out of your data. It gives you a nice flavor of several techniques used throughout all process of knowledge discovery (and not only mining techniques). Moreover, if bought with the software option you can quickly try several methods on your data. The book is very easy to read in spite of addressing some though research problems.
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Not that practical!
If you are new to data mining, you probably won't grab a global view of it with this book. According to the authors, it is not the objective, they want it to be a practical guide. Lesen Sie weiter...
Veröffentlicht am 6. November 1998 von Mapun Dungun
Excellent introduction to the topic
Thoughtful and readable introduction to data mining. It is a useful primer and refreshingly devoid of the buzzword afflictions of other books on this topic.
Am 10. September 1998 veröffentlicht
Reasonably good introduction
This isn't a bad book to pick up if you want to find out what data mining is about. I did, and it served as a good introduction. Lesen Sie weiter...
Am 25. Mai 1998 veröffentlicht
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